Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction Better than 86% of Optimal

Hart, William E.; Istrail, Sorin

doi:10.1089/cmb.1997.4.241

Cited by 40 publications

(10 citation statements)

References 9 publications

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“…enum Approximation algorithms Hart & Istrail [29] cubic HP 3 -approx. 3/8 of optimum Hart & Istrail [28] FCC-HP side chain 3 -approx. 86% of optimum Agarwala et al [3] FCC-HP 3 -approx.…”

Section: Resultsmentioning

confidence: 99%

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

Backofen

Will

2006

Constraints

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Simplified protein models are used for investigating general properties of proteins and principles of protein folding. Furthermore, they are suited for hierarchical approaches to protein structure prediction. A well known protein model is the HP-model of Lau and Dill [Lau, K. F., & Dill, K. A. (1989)]. A lattice statistical mechanics model of the conformational and sequence spaces of proteins. Macromolecules, 22, 3986 -3997) which models the important aspect of hydrophobicity. One can define the HP-model for various lattices, among them two-dimensional and three-dimensional ones. Here, we investigate the three-dimensional case. The main motivation for studying simplified protein models is to be able to predict model structures much more quickly and more accurately than is possible for real proteins. However, up to now there was a dilemma: the algorithmically tractable, simple protein models can not model real protein structures with good quality and introduce strong artifacts.We present a constraint-based method that largely improves this situation. It outperforms all existing approaches for lattice protein folding in HP-models. This approach is the first one that can be applied to two three-dimensional lattices, namely the cubic lattice and the face-centered-cubic (FCC) lattice. Moreover, it is the only exact method for the FCC lattice. The ability to use the FCC lattice is a significant improvement over the cubic lattice. The key to our approach is the ability to compute maximally compact sets of points (used as hydrophobic cores), which we accomplish for the first time for the FCC lattice.

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“…enum Approximation algorithms Hart & Istrail [29] cubic HP 3 -approx. 3/8 of optimum Hart & Istrail [28] FCC-HP side chain 3 -approx. 86% of optimum Agarwala et al [3] FCC-HP 3 -approx.…”

Section: Resultsmentioning

confidence: 99%

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

Backofen

Will

2006

Constraints

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“…This so called HP model [84] has been extensively studied by Chan and Dill [85 -94], Sali and coworkers [95 -97], Shakhnovich and coworkers [27], Karplus and coworkers [21,96,97] and many others [24,98 -106]. Modifications of this model include different codes for sequence [23,95,107 -121] (from a simple collapsing homopolymer to full twenty-residue types of sequences [117,122]), more complex (and more realistic) interaction schemes [23,25,114,116,118,[122][123][124][125][126][127][128] effects of other molecules [66,90,[129][130][131][132][133][134][135] a simple lattice representation of the side chains [62,128,133,136 -140], and modifications of the geometry of the HP model [98,141,142]. An excellent review of earlier studies of this model can be found in work of Dill et al [20].…”

Section: Simple Lattice Models Of Protein-like Polypeptidesmentioning

confidence: 99%

“…Typical examples for this kind of approach are high coordination lattice based methods developed by Kolinski and Skolnick and coworkers [56,74,81,189,273,316,319] (the previously described SICHO and CABS models) and continuous space models [208], where a good example is the UNRES model of Scheraga and coworkers [42,133,212]. The high coordination lattice models heavily rely on knowledge-based statistical potentials [316] (that generalize structural regularities seen in real proteins) while the UNRES force field was designed and optimized basing on more rigorous physical principles [41,42,133,212]. A successful application of the above mentioned lattice models to the nontrivial cases of protein structure predictions requires substantial support from threading that provides a prediction of some fraction of native side chain contacts and short range native distances along the polypeptide chain [34,35,55 -57,273,316,319].…”

Section: Applications Of Moderate Resolution and 'High Resolution' Rementioning

confidence: 99%

Reduced models of proteins and their applications

Koliński

Skolnick

2004

Polymer

175

143

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Reduced computer modeling of proteins now has a history of about 30 years. In spite of the enormous increase in computing abilities, reduced models are still very important tools for theoretical studies of protein structure, dynamics and thermodynamics. Very simple, highly idealized lattice (and recently also off-lattice) models could be studied in great detail, providing valuable insight into the most general factors governing structure stability, folding kinetics and interactions responsible for characteristic two-state behavior near the folding temperature. More complex models now enable modeling of real proteins on the level of low to moderate resolution, allowing us to address more detailed questions. Ab initio protein structure predictions, still being far from a routine task, have become feasible. When supported by evolutionary information from multiple sequence alignments and potential local and/or global structural similarity to known structures, reduced modeling opens up new areas of comparative modeling, thereby complementing contemporary structural genomics. q

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“…see [3,5,7,9,[13][14][15][16][17]22,23,26,28]. This problem can be investigated at two complementary levels.…”

Section: Introduction and Problem Definitionsmentioning

confidence: 99%

The inverse protein folding problem on 2D and 3D lattices

Berman

DasGupta

Mubayi

et al. 2007

Discrete Applied Mathematics

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In this paper we investigate the inverse protein folding (IPF) problem under the Canonical model on 3D and 2D lattices [W.E. Hart, On the computational complexity of sequence design problems, E.I. Shakhnovich, A.M. Gutin, Engineering of stable and fast-folding sequences of model proteins, Proc. Natl. Acad. Sci. 90 (1993) 7195-7199]. In this problem, we are given a contact graph G = (V , E) of a protein sequence that is embeddable in a 3D (respectively, 2D) lattice and an integer 1 K |V |. The goal is to find an induced subgraph of G of at most K vertices with the maximum number of edges. In this paper, we prove the following results:• An earlier proof of NP-completeness of the IPF problem on 3D lattices [W.E. Hart, On the computational complexity of sequence design problems, ] is based on the NP-completeness of the IPF problem on the 2D lattices. However, the reduction was not correct and we show that the IPF problem for 2D lattices can be solved in O(K|V |) time. But, we show that the IPF problem on 3D lattices is indeed NP-complete by a providing a different reduction from a different NP-complete problem. • We design a polynomial-time approximation scheme for the IPF problem on 3D lattices using the shifted slice-and-dice approach in Mass, Approximation schemes for covering and packing problems in image processing and VLSI, J. ACM 32(1) (1985) 130-136], thereby improving the previous best polynomial-time approximation algorithm which had a performance ratio of 1 2 [W.E. Hart, ଁ A preliminary version of this paper without many

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Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction Better than 86% of Optimal

Cited by 40 publications

References 9 publications

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

Reduced models of proteins and their applications

The inverse protein folding problem on 2D and 3D lattices

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